COURSE SUMMARY
Course Title: 
Optimization Techniques
Course Code: 
18SC712
Year Taught: 
2019
Degree: 
Postgraduate (PG)
School: 
School of Engineering
Campus: 
Coimbatore

'Optimization Techniques' is an elective course offered in M. Tech. program in Structural & Construction Engineering at the School of Engineering, Amrita Vishwa Vidyapeetham, Coimbatore campus.

Introduction to Optimization: Engineering application of Optimization – Statement of an optimization problem- Optimal Problem formulation – Classification of optimization problems. Definition of Global and Local minima. Unconstrained Optimization: Optimality Conditions- Algorithms for univariate optimization- Algorithms for multivariate optimization- Convergence of algorithms – Engineering applications of unconstrained algorithms. Lagrange multiplier Theory & Duality: Lagrange Multipliers- Kuhn- Tucker Optimality Conditions and sufficiency for convex problems- Lagrangian duality- Saddle point conditions. Constrained Optimization: Optimality conditions- Feasible direction methods- Frank- Wolfe algorithm- Gradient Projection – Active set methods- Penalty function methods- Constrained steepest descent method. Modern methods of optimization: Genetic Algorithms- Simulated Annealing – Tabu search – Ant Colony optimization – Particle Swarm Optimization – Neural- Network based Optimization – Fuzzy optimization techniques. Introduction to Multi – Objective optimization – Classical methods- Pareto Optimality – Use of evolutionary algorithms for solving Multi Objective optimization problems. - Lab Practice: Use of programming languages and Matlab to solve optimization problems.

  • Optimization for Engineering Design Algorithms and Examples, Prentice Hall, 2012.
  • Engineering Optimization Theory and Practice, Rao S. S, Third Edition, New Age International, 2010.
  • Manufacturing Optimization Through Intelligent Techniques, Saravanan. R, Taylor and Fransis, 2006.
  • Operations Research Principles and Practice, Ravindran, Phillips and Solberg, Wiley India, 2007.
  • Non Linear and Dynamic Programming, Hadley. G, Addison Wesley, 1964.